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FAVoR: Measuring and Mitigating Author-Style Homogenization in Federated Personalized Generation
Large language models are increasingly used as personalized writing assistants, but adapting a model across many authors can compromise individual writing style by pulling author-specific signals toward a shared register. Federated parameter-efficient fine-tuning (PEFT) offers a data-local setting f
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